2014 – Flow shop scheduling with heterogeneous workers


Online supplement to:

Benavides, A. J., Ritt, M., & Miralles, C. (2014). Flow shop scheduling with heterogeneous workers. European Journal of Operational Research, 237(2), 713-720. doi:10.1016/j.ejor.2014.02.012.

Mirror: http://inf.ufrgs.br/algopt/hetFS/

Abstract

We propose an extension to the flow shop scheduling problem named Heterogeneous Flow Shop Scheduling Problem (Het-FSSP), where two simultaneous issues have to be resolved: finding the best worker assignment to the workstations, and solving the corresponding scheduling problem. This problem is motivated by Sheltered Work centers for Disabled, whose main objective is the labor integration of persons with disabilities, an important aim not only for these centers but for any company desiring to overcome the traditional standardized vision of the workforce. In such a scenario the goal is to maintain high productivity levels by minimizing the maximum completion time, while respecting the diverse capabilities and paces of the heterogeneous workers, which increases the complexity of finding an optimal schedule. We present a mathematical model that extends a flow shop model to admit a heterogeneous worker assignment, and propose a heuristic based on scatter search and path relinking to solve the problem. Computational results show that this approach finds good solutions within a short time, providing the production managers with practical approaches for this combined assignment and scheduling problem.

BibTEX

@article{Benavides2014hetFSSP,
title={Flow shop scheduling with heterogeneous workers},
author={Benavides, Alexander J. and Ritt, Marcus and Miralles, Crist{\'o}bal},
journal={European Journal of Operational Research},
year={2014},
volume={237},
number={2},
pages={713--720},
publisher={Elsevier},
doi={10.1016/j.ejor.2014.02.012}
}

Authors

Alexander J. Benavides, Marcus Ritt, Cristobal Miralles.

Downloads

Below you can download the following data files for the heterogeneous flow shop scheduling problem:

  1. Instances based on Carlier and Taillard.

  2. Detailed paper results.

  3. Best known solutions from the paper.

  4. Source code.